Background
The injection of formalin into the skin of rodent hind paws to cause spontaneous pain-related (nocifensive) behaviors is one of the most commonly used animal pain assays [
1]. This test was introduced in 1977 as a method that allowed nocifensive behaviors to be studied without restraint, and with a continuous rather than transient source of stimulation [
2]. This model can be distinguished from many other irritant pain models--for example, ones involving the administration of carrageenan, bee venom, capsaicin and other compounds--by the existence of a biphasic response. An intense first (early) phase of hindpaw shaking and licking subsides approximately 5-10 minutes after formalin injection, only to have the behaviors reappear and last another 30 minutes or longer. The first phase of this test is thought to be due to direct effects of formalin on nociceptive fibers [
3], and recent evidence suggests that the Transient receptor potential cation channel 1 (TRPA1) receptor/ion channel might mediate that signal transduction; TRPA1-deficient mice and mice administered a selective TRPA1 antagonist display greatly reduced early phase formalin-induced behaviors [
4]. Formalin early phase behavior are sensitive to reversal by analgesics such as opioids and paracetamol [
3,
5].
The second (late) phase of the formalin response, sometimes referred to as the "inflammatory phase," has classically been ascribed to inflammation as non-steroidal anti-inflammatory drugs such as acetylsalicylic acid, ibuprofen and ketoprofen are active in reducing the associated behaviors [
5,
6]. However, many drugs without anti-inflammatory activity are also active in this phase including gabapentin, lamotrigine, nitric oxide synthase (NOS) inhibitors and others [
7,
8]. Further exploration of the basis for late phase nocifensive behaviors has revealed that sensitization of dorsal horn neurons is involved [
9,
10]. In fact, the intrathecal injection of many agents reduces late phase behaviors. Late phase behavior is also of interest because of the similarities in presumed mechanism between it and some dimensions of neuropathic pain [
11].
Large inter-individual differences exist between both humans and animals with respect to pain, nociceptive sensitivity and analgesic responses [
12]. That genetics mediates a significant percentage of inter-strain variance in commonly used mouse pain assays has been firmly established. The formalin test when applied to inbred mice leads to highly strain-dependent results for both early and late phase behaviors [
13,
14]. Such inter-strain differences have been exploited using quantitative trait locus (QTL) mapping, haplotypic analysis and other techniques to gain insight into the identity of the trait-relevant genes. For example, one recent report used both QTL and haplotypic analyses to demonstrate that the early phase of the formalin response was dependent on the activity of afferent neuron ATPase activity, presumably related to the ability of the neuron to maintain an electrochemical gradient supporting neuronal firing [
15]. The heuristic value of the approach was illustrated by the fact that the relevant gene was
Atp1b3 [
15], encoding a little-studied β subunit of the ATPase rather than the catalytic α subunit. Genetics based studies have not yet been published demonstrating how particular genes might be responsible for the wide differences between strains in their late phase behavior despite the importance of this response.
An alternative technique for identifying genes potentially involved in regulating a phenotype of interest is to correlate expression of the phenotype, such as a pain-related nocifensive behavior, with the expression level of genes in a tissue known to take part in controlling the phenotype [
16,
17]. The assumptions underlying this approach are that the abundance of mRNA for at least some controlling genes will be either positively or negatively correlated with the phenotype of interest, and that the correlation reflects a functional role for the gene in the phenotype. This "expression QTL" or "genetical genomics" technique is particularly attractive as any number of phenotypes could be compared with expression databases for specific tissues. Here we use such an approach to identify candidate genes controlling late phase formalin induced nocifensive behavior in inbred strains of mice.
Discussion
The goal of the present studies was to use the emerging technique of correlating pain-related (nocifensive) behavior across multiple strains of inbred mice with genome-wide gene expression in a tissue known to regulate that behavior (i.e., an eQTL or genetical genomics approach). In this case, the late phase of formalin-induced nocifensive behavior was correlated with spinal cord gene expression for 10 strains of mice. Subsequently, 4 additional strains were evaluated in experiments designed to test the correlational results. The results of our correlational studies identified several genes with strongly associated spinal expression patterns. Remarkably, 4 out of the top 5 most-strongly associated genes, or closely related members of their gene families, had previously been demonstrated to have links to pain and analgesia. Subsequent use of mRNA and protein analysis in additional strains confirmed the correlational observations for Mapk8 (protein known as JNK1), a spinal cord gene with known roles in neuroplasticity. Finally a selective JNK inhibitor blocked late phase formalin behaviors strongly, with no effect whatsoever on early phase behaviors. In retrospect, no early phase effects of this drug could be expected, as there was no statistical correlation between the early phase and late phase behaviors across the strains tested. Thus, working with expression and behavioral databases for a relatively modest number of mouse strains allowed us to identify highly plausible functionally related genes. The total number of inbred strains required for these experiments was low compared to the numbers typically involved in genetic based approaches such as QTL or haplotypic analyses.
The gene chosen for confirmatory experiments,
Mapk8, has well-established roles in intracellular signaling, including signaling related to nociception. An early report by Yang et al. [
20] used microarray analysis on rat spinal cord dorsal horn tissue after peripheral axotomy to identify JNK1 and other members of the JNK family as upregulated after nerve injury, though a functional role for these changes was not demonstrated. Subsequent experiments confirmed that the three splice variants of JNK (JNK1-3) are highly expressed in spinal cord tissue [
10]. Using spinal nerve ligation to create a model of neuropathic pain, Zhuang et al. demonstrated that the up-regulation of JNK1 occurred primarily in spinal astrocytes, and that the spinal administration of a selective JNK1 inhibitor blocked the resulting hypersensitivity [
21]. Other experiments showed that selective JNK inhibition reduced nociceptive sensitization in a model of diabetic neuropathy [
22] and after bee venom or capsaicin injection [
23,
24]. The suggested mechanism for activation of JNK1 is via transforming growth factor-activated kinase 1 (TAK1), a member of the MAPK kinase family. Spinal knock-down of TAK1 reduces astrocytic JNK1 phosphorylation in spinal cord tissue after nerve injury [
25]. Additional evidence suggests that spinal TNFα may work through JNK1 to produce the cytokine MCP-1, ultimately sensitizing spinal dorsal horn neurons [
26].
Overall, the JNK family of MAPK genes is perhaps the least well-studied of the MAPK gene superfamily. Hassanzadeh et al. demonstrated that this gene was required for the appearance of spinal cord "dark neurons" after peripheral formalin injection, neurons which are thought to have undergone excitotoxic injury [
27]. It does appear that spinal cord dorsal horn astrocytes are activated after peripheral formalin injection [
28]; astrocytes may be the primary site of spinal
Mapk8 expression as noted above. To our knowledge, the role of
Mapk8/JNK1 in regulating late phase formalin behavior has not been well studied. Our experiments are, therefore, the first to demonstrate directly a role for
Mapk8/JNK1 in spinal cord sensitization after formalin injection.
One interesting feature of our findings was the inverse correlation of spinal cord
Mapk8 mRNA and JNK1 protein levels. Thus mouse strains with higher licking times had greater spinal cord JNK1 protein levels as expected, based on the reported relationship between JNK1 function and pain behaviors in other models. In addition, blockade of JNK using a selective agent reduced late phase formalin licking behavior. However, as demonstrated by the negative correlation coefficient for the mRNA-behavior relationship in Table
2 and confirmatory data in Figure
3, the behaviorally higher responding strains had lower
Mapk8 mRNA levels. These observations suggest that the steady state levels of JNK1 are controlled by factors other than transcription. One possible factor would be the protein's high stability resulting in a low turnover rate, as JNK1 is constitutively expressed in the spinal cord [
21]. Therefore, relatively low levels of
Mapk8 mRNA would be necessary to maintain the steady state levels of the protein. Another possibility would be that the genetic factor(s) explaining the inter-strain formalin behavioral differences might involve control of translation rather than transcription. In this scenario, genetically regulated enhancement of translation may lead to high protein levels with compensatory reduction in transcriptional activity thus lowering mRNA levels. Control of translation is a complex process [
29]. Though our studies did not specifically address mechanisms which could explain this phenomenon, micro RNA (miRNA) is an example of a type of regulatory molecule potentially enhancing translation of multiple genes simultaneously. Alternatively, under basal conditions the
Mapk8 would be under negative regulation by the JNK1 and its substrates, as intense and prolonged JNK activation would result in programmed cell death[
30]. Members of the MKKs (MAPK kinases) which activate JNK pathway are themselves under negative regulation by substrates of JNK, whilst MKPs (MAP kinase phosphatase) which inhibit the pathway are positively regulated by some of the same substrates [
31,
32]. It is notable that our haplotypic analysis was only weakly suggestive of a role for
Mapk8 genetics in controlling late phase formalin behavior. In fact two of the other associated genes also had strongly negative correlations between mRNA levels and behavior.
While our experiments focused on
Mapk8, one other gene (
Pla2g4e) was statistically even more closely linked to formalin test second phase behaviors. This gene codes for a cytosolic form of phospholipase A2 (PLA2), an enzyme family with strong links to inflammatory pain. PLA2 serves to liberate arachidonic acid which is subsequently metabolized by cyclooxygenase 1 and 2 (COX1/COX2) to form pro-nociceptive prostanoids, although arachidonic acid is a substrate in other pathways as well. This enzyme family is comprised of approximately 15 groups and four main types, including the secreted sPLA2, cytosolic cPLA2, calcium-independent iPLA2, and platelet activating factor (PAF) [
33]. Though the
Pla2g4e isoform has not been examined specifically in pain models, cytosolic PLA2 probably does contribute to spinal sensitization in several models of pain. For example, the cytosolic PLA2 inhibitor, AACOCF3, reduced both nociceptive sensitization and spinal arachidonic acid production in the spinal cord tissue of rats used in the chronic constriction injury model of neuropathic pain [
34]. In another set of experiments it was demonstrated that antisense knockdown of spinal cytosolic group 4a PLA2 reduced late but not early phase formalin-induced pain behaviors [
35]. This form of phospholipase A2 is the predominant one in spinal cord tissue [
36]. In the same group of studies it was determined that spinal cord dorsal horn neurons may be the predominant site of spinal expression of this enzyme. While the results from our study associated a distinct member of the same cytosolic type of PLA2, independent confirmation of this association is required. Unfortunately the pharmacological and immunohistochemical tools currently available would not provide definitive evidence for the participation of
Pla2g4e in late phase formalin behavior, and it is likely that experiments with knockout mice or spinal knock-down would need to be performed.
Another associated gene with pre-existing data linking its function to formalin late phase behaviors is the
Scn2b gene coding for the sodium ion channel β
2 subunit. The β subunits of sodium ion channels modulate the kinetics and other electrical properties of sodium ion channels [
37]. In a recent report in which
Scn2b knockout animals and neurons derived from these animals were studied, it was discovered that
Scn2b deletion both reduced TTX-sensitive sodium ion currents in small diameter neurons, and the expression of specific sodium ion channels, notably Na
V1.7 [
38]. Critically, gene deletion reduced late phase formalin behaviors without altering early phase responses. Interestingly, Na
V1.7 is an ion channel whose dysfunction in humans has been associated with either pain hypersensitivity or insensitivity depending on the type of genetic alteration present [
39].
Methods
Animals
Mice for all experiments were purchased from The Jackson Laboratory (Bar Harbor, ME) at 6-12 weeks of age, or bred in-house from stock mice so obtained. Upon weaning (at 18-21 d) or immediately after arrival, mice were housed in standard shoebox cages of 2-4 with same sex littermates in a temperature-controlled (20° ± 1°C) environment (14 h: 10 h light/dark cycle; lights on at 07:00 h), and with ad lib access to food and water. Purchased mice were habituated to the laboratory for at least one week before any behavioral testing commenced. Husbandry conditions were similar for mice housed at the McGill University and Palo Alto VA Medical Center (VAPAHCS). All experiments were approved by the local Institutional Animal Care and Use Committees of McGill University and VAPAHCS.
Mice were habituated in individual transparent Plexiglas cylinders prior to a subcutaneous injection of 5% formalin into the plantar right hindpaw (20 μl volume). Following injection mice were digitally videotaped from underneath a glass floor for 60 min, or directly observed. Video files were later sampled for 5 s at 1-min intervals, and the presence or absence of right hindpaw licking/biting nocifensive behaviors in that 5-s period was scored using Observer software (Noldus, Leesburg, VA). Direct observations timed the licking/biting behavior using a stopwatch. The early phase of the formalin test was defined as 0-5 min post-injection, and the late phase as 10-60 min post-injection. These data were tabulated as the percent of samples licking during the specified intervals. In pharmacological experiments mice were continuously observed providing the total number of seconds spent licking/biting in each phase for each animal.
Drug administration
The non peptide JNK inhibitor, SP600125 (anthra [1,9-cd]pyrazol-6(2H)-one), was purchased from Sigma (St. Louis, MO) and prepared in DMSO (20% final concentration). Intrathecal (
i.t.) injections of 5 μl of SP600125 or vehicle (20% DMSO) were made under brief isofluorane anesthesia with a 30-gauge needle between the L5 and L6 level as we have described previously[
17]. The SP600125 dose of 50 nmol was chosen from the results of pilot experiments showing this to be a dose providing maximal effect on late phase formalin behaviors, and from the available literature [
21]. Formalin injections were performed 3 h after
i.t. drug injections at which time drug effect was found to be maximal, in agreement with published data [
21].
Expression analysis of mouse spinal cord tissue
Microarray analyses were performed using Affymetrix GeneChip Mouse Genome 430 2.0 Array (>39,000 transcripts) using previously described methods [
40]. Spinal cords were prepared from 3 experimentally naïve mice from each of the following 10 inbred strains: 129/SvIm, AKR, B10.D2-H2/oSNJ, BALB/c, C3H/He, C57BL/6, DBA/2, LP, MRL/Mp, NZW/LaC (all "J" substrains). The probe intensity data generated from all 30 arrays were read into the R software environment
http://www.R-project.org directly from .CEL files using the R/affy package [
41], which was also used to extract and manipulate probe level data to assess data quality and to create expression summary measures. Normalization was carried out using the robust multiarray average (RMA) method [
42] to form one expression measure for each probeset on each array.
Each array has 45,101 probesets, which correspond to >39,000 transcripts. The following analyses were applied to identify probesets that were differentially expressed between strains (with a >3-fold difference). A one-way ANOVA model was applied to test whether the probeset was differentially expressed among the mouse strains. The average expression level for each probeset for each strain was calculated. Since RMA signals are on log2 scale, the fold change was defined as 2 to the power of the maximum average expression level minus the minimum expression level. Probesets with ANOVA p < 0.01 and a fold change greater than 3 were identified as genes that were significantly differentially expressed. There were 2,500 probesets that met these criteria, and these were selected for further correlational analysis with the formalin test late phase data.
Correlational analysis of spinal cord expression and mouse behavioral data
We assessed the extent of correlation between each selected differentially expressed probeset and the phenotypes of interest using Pearson's correlation coefficient [
43]. For each probeset, the RMA signal intensity (at log2 scale) was used for the correlation calculation. The probesets were then ordered by the absolute value of the correlation coefficient.
Genomic analysis
The SNP data provided by Frazer at al. were used to identify the haplotypic structure around the
Mapk8 gene [
18]. Twelve strains were represented in this database. In addition, BALB/cBy data were available, and though we actually tested BALB/c mice, these substrains were considered genetically similar enough to include them in our haplotypic analysis. The murine
Mapk8 gene is located on chromosome 14 from 34,191,084 to 34,260,344 bp (
http://www.ensembl.org, Mouse Genome Build 37). SNP data were downloaded from
http://mouse.perlegen.com/mouse/index.html, and all SNPs that were within 2,000 bp of the
Mapk8 region were identified. There were 86 SNPs that were specific to the 8 strains within this genomic region, which included the whole
Mapk8 gene. The haplotypic structure of this region was then visualized in Excel using a simple coloring scheme.
Halpotypic analysis was performed as outlined by Wang et al. [
19] using the strain specific
Mapk8 associated haplotype alleles. To test the degree of correlation between the strain data and the allelic identities an ANOVA based approach was used.
Expression analysis (mRNA)
Mice were killed at specific time points by CO
2 asphyxiation without prior exposure to formalin. Spinal cord tissue was harvested by extrusion. Lumbar spinal cord segments were dissected on a chilled surface. Dissected tissue was then quick-frozen in liquid nitrogen and stored at -80°C until use. For PCR experiments, total RNA was isolated using the RNeasy Mini Kit (Qiagen, Valencia, CA) according to the manufacturer's instructions. The purity and concentration were determined spectrophotometrically as described previously for brain and spinal cord samples [
44]. In the next step cDNA was synthesized from1 μg total RNA using random hexamer priming and a First Strand cDNA Synthesis Kit (Invitrogen, Carlsbad, CA) according to the manufacturer's instructions. Quantitative PCR reactions were conducted in a volume of 4 μl using the Sybr Green I master kit (PE applied Biosystems, Foster City, CA). Using an ABI prism 7900HT system (Applied Biosystems, Foster City, California, USA), PCR was carried out using the parameters 52°C, 5 min->95°C, 10 min then (95°C, 30 s->60°C, 60 s) for 40 cycles. The sequences for the
Mapk8 primers were (forward primer) GCCACAAATCCTCTTTCCA and (reverse primer) CACATCGGGGAACAGTTTCT. Samples were analyzed in triplicate. Melting curves were performed to document single product formation.
Quantification was accomplished according to the standard curve method as described by the PCR system manufacturer (PE Applied Biosystems) as we have used previously [
45]. In order to achieve the same PCR efficiency for each analyte, serial dilution of cDNA was used to construct standards curve for
Mapk8 and 18S RNA which was used as a control. The
r2 values for the standard curves of the genes approached 1.0, suggesting the same amplification efficiency in the PCR reactions under these conditions.
Expression analysis (protein)
Lumbar spinal cord tissue was homogenized in SDS Lyses sample Buffer, 100 mg tissue to 1 ml sample lysis buffer mix (1.25 ml of 0.5 M Tris -HCL pH 6.8, 1 ml of glycerol, 1 ml of 20% SDS, 69 μl of β-mercaptoethanol, 6.68 ml distilled water, total 10 ml). Tissue was then vortexed followed by boiling for 8 min, then cooling on ice. The homogenate was centrifuged at 12,000 × g for 10 min at 4°C. The supernatant was collected and retained for Western blot analyses. The concentration of protein in the supernatant was measured using the DC Protein Assay kit (Bio-Rad, Hercules, CA). Equal amounts of protein (50 μg) were sized fractionated by electrophoresis on 10% acrylamide gels (Bio-Rad) and transferred onto LI-COR Odyssey Nitrocellulose Membrane (LI-COR Biosciences, Lincoln, NE). The blot was blocked for overnight in LI-COR Odyssey Blocking Buffer followed by incubation with a mixture of primary antibodies. JNK1 affinity purified rabbit polyclonal antibody was used at 1:500 dilution (Abgent, San Diego, CA) and actin mouse monoclonal antibody at 1:1000 dilution (Santa Cruz Biotechnology, Inc., Santa Cruz, CA) with incubation on a rocking platform at 4°C for 24 h. After washing, the blots were incubated 2 h at room temperature in a secondary antibody mix: IRDYE 680 donkey anti-mouse IgG (LI-COR) and IRDYE 800CW goat anti rabbit IgG (LI-COR) at 1:20,000 dilution for each. The blots were washed and placed in a LI-COR Odyssey Infrared Imaging System. Bands specific to each protein were quantified from the same gels and analyzed with LI-COR software.
Statistical analysis
Frequency of, or total time spent licking the hindpaw as well as the time course data were analyzed by two-way ANOVA followed by post-hoc Bonferroni multiple comparison tests. A criterion α = 0.05 was employed. For expression analysis (mRNA and protein) experiments samples from n = 4 mice per strain were analyzed in triplicate. The values from three strains within each group (replicates) were compared to other strain group (High vs. low responding) by unpaired t-Test.
Competing interests
The authors declare that they have no competing interests.
Authors' contributions
XL performed all of the molecular biology and expression studies. PS performed the JNK inhibitor experiments and revised the manuscript. MZ identified the Mapk8 SNPs, determined the strain specific haplotype construction and was involved in constructing the spinal cord gene expression database. JR performed the multi-strain formalin testing experiments. GP designed and supervised the construction of the gene expression database and analysis. He also supervised the genetic analysis components of the project. JSM supervised the design of the primary multi-strain formalin testing and processing of those data. Also, he assisted in the design of the subsequent experimentation and interpretation of the resulting data. JDC coordinated the various aspects of the project and directly supervised the expression analysis and inhibitor studies.
All authors read and approved the final manuscript.